


import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil


@pytest.fixture
def 							__lowerCAmelCase      (			__magic_name__      ):
 _lowercase:       Optional[Any]						=				tmp_path / 'file.csv'
 _lowercase:       Optional[Any]						=				textwrap.dedent(
     "\\n        header1,header2\n        1,2\n        10,20\n        "      )
 with open(a__ ,   "w"      ) as f:
  f.write(a__      )
 return str(a__      )


@pytest.fixture
def 							__lowerCAmelCase      (			__magic_name__      ):
 _lowercase:       Union[str, Any]						=				tmp_path / 'malformed_file.csv'
 _lowercase:       Tuple						=				textwrap.dedent(
     "\\n        header1,header2\n        1,2\n        10,20,\n        "      )
 with open(a__ ,   "w"      ) as f:
  f.write(a__      )
 return str(a__      )


@pytest.fixture
def 							__lowerCAmelCase      (			__magic_name__ ,   __magic_name__      ):
 _lowercase:       Dict						=				tmp_path / 'csv_with_image.csv'
 _lowercase:       Optional[int]						=				textwrap.dedent(
     f"\\n        image\n        {image_file}\n        "      )
 with open(a__ ,   "w"      ) as f:
  f.write(a__      )
 return str(a__      )


@pytest.fixture
def 							__lowerCAmelCase      (			__magic_name__      ):
 _lowercase:       Optional[Any]						=				tmp_path / 'csv_with_label.csv'
 _lowercase:       Any						=				textwrap.dedent(
     "\\n        label\n        good\n        bad\n        good\n        "      )
 with open(a__ ,   "w"      ) as f:
  f.write(a__      )
 return str(a__      )


@pytest.fixture
def 							__lowerCAmelCase      (			__magic_name__      ):
 _lowercase:       Tuple						=				tmp_path / 'csv_with_int_list.csv'
 _lowercase:       Tuple						=				textwrap.dedent(
     "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        "      )
 with open(a__ ,   "w"      ) as f:
  f.write(a__      )
 return str(a__      )


def 							__lowerCAmelCase      (			__magic_name__ ,   __magic_name__ ,   __magic_name__      ):
 _lowercase:       Optional[int]						=				Csv()
 _lowercase:       Tuple						=				csv._generate_tables([[csv_file, malformed_csv_file]]      )
 with pytest.raises(a__ ,   match="Error tokenizing data"      ):
  for _ in generator:
   pass
 assert any(
     record.levelname == "ERROR"
     and "Failed to read file" in record.message
     and os.path.basename(a__      ) in record.message
     for record in caplog.records      )


@require_pil
def 							__lowerCAmelCase      (			__magic_name__      ):






 with open(a__ ,   encoding="utf-8"      ) as f:
  _lowercase:       str						=				f.read().splitlines()[1]
 _lowercase:       Tuple						=				Csv(encoding="utf-8" ,   features=Features({"image": Image()}      )      )
 _lowercase:       Optional[int]						=				csv._generate_tables([[csv_file_with_image]]      )
 _lowercase:       Any						=				pa.concat_tables([table for _, table in generator]      )
 assert pa_table.schema.field("image"      ).type == Image()()
 _lowercase:       Optional[int]						=				pa_table.to_pydict()['image']
 assert generated_content == [{"path": image_file, "bytes": None}]


def 							__lowerCAmelCase      (			__magic_name__      ):






 with open(a__ ,   encoding="utf-8"      ) as f:
  _lowercase:       Tuple						=				f.read().splitlines()[1:]
 _lowercase:       List[Any]						=				Csv(encoding="utf-8" ,   features=Features({"label": ClassLabel(names=["good", "bad"]      )}      )      )
 _lowercase:       List[Any]						=				csv._generate_tables([[csv_file_with_label]]      )
 _lowercase:       List[str]						=				pa.concat_tables([table for _, table in generator]      )
 assert pa_table.schema.field("label"      ).type == ClassLabel(names=["good", "bad"]      )()
 _lowercase:       str						=				pa_table.to_pydict()['label']
 assert generated_content == [ClassLabel(names=["good", "bad"]      ).straint(a__      ) for label in labels]





def 							__lowerCAmelCase      (			__magic_name__      ):
 _lowercase:       Optional[Any]						=				Csv(encoding="utf-8" ,   sep="," ,   converters={"int_list": lambda __magic_name__      : [int(a__      ) for i in x.split()]}      )
 _lowercase:       int						=				csv._generate_tables([[csv_file_with_int_list]]      )
 _lowercase:       Any						=				pa.concat_tables([table for _, table in generator]      )
 assert pa.types.is_list(pa_table.schema.field("int_list"      ).type      )
 _lowercase:       Tuple						=				pa_table.to_pydict()['int_list']
 assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]









"""simple docstring"""


from abc import ABC, abstractmethod
from argparse import ArgumentParser




class 						__UpperCamelCase     (     UpperCamelCase						):
					@staticmethod
					@abstractmethod
					def        UpperCAmelCase__ (							UpperCAmelCase							:	ArgumentParser   )	->       Optional[Any]:
											raise NotImplementedError()
					@abstractmethod
					def        UpperCAmelCase__ (							self							:	str   )	->       List[str]:
											raise NotImplementedError()